Artificial intelligence-powered women’s healthcare sounds revolutionary—until you realize it’s being trained on decades of data where women’s symptoms were dismissed and downplayed. Recent MIT and London School of Economics and Political Science research found that AI tools used in hospitals systematically downplay symptoms in women and ethnic minorities, recommending lower levels of care for female patients. Those findings reinforce what Kathrin Folkendt founder, of Femtech Insider has warned for years: “AI was supposed to fix healthcare bias. Instead, it’s making it worse for women.”
That failure is exactly what Amanda Ducach set out to change. Her company, Ema, built an AI-powered women’s health platform that listens differently, learns from women’s experiences, and guides care responsibly.
How Empathy Inspired An AI-Powered Women’s Health Platform
Ducach’s belief that empathy and technology can coexist began at home. The daughter of an Argentinian immigrant physician, she learned early “the importance of hard work.” Before founding Ema, she worked on racial and ethnic health disparities, which gave her a firsthand understanding of how bias affects who receives care and who doesn’t.
Her first venture, SocialMama, was a peer-to-peer platform connecting women who shared similar experiences. “Women were helping each other through hard moments and giving a lot of health advice,” she describes. “We added physicians to make sure it stayed evidence-based. That’s when we realized we could use AI to scale empathy.”
That realization led to Ema—a conversational platform trained to understand how women talk about their bodies, pain, and emotions.
Training AI For Women’s Health
Ema’s model is trained on medically curated data and millions of women’s health interactions, capturing the nuances of how women describe physical and emotional experiences. “We knew that women use different words to describe how they feel,” Ducach noted. “If AI doesn’t understand that language, it will fail them.”
Research continues to highlight the high stakes. Recent studies have quantified how data and algorithm design can exacerbate health disparities across gender and racial lines. Those results substantiate the importance of Ema’s approach—training AI to learn from women’s lived realities, rather than from datasets built around male norms.
Ema’s reach is already expanding. Its AI is embedded in other women’s health platforms, such as Willow, where it supports postpartum wellness and maternal health. The company’s long-term vision is to serve women across every stage of life, from menstruation to post menopause, offering medically vetted, emotionally intelligent guidance.
Governance and transparency are built into that foundation. The platform monitors for bias, keeps detailed records of its recommendations, and runs everything past clinicians to verify that it aligns with medical evidence. Ema also helps hospitals, employers, and health startups navigate the ethical side—teaching them about data privacy, holding algorithms accountable, and preventing bias.
“We’re often the thought partner as much as the technology provider,” Ducach says. “Companies come to us for the infrastructure, but what they also need is help making sure their AI is safe, compliant, and fair.”
Why An AI-Powered Women’s Health Platform Matters Now
Women live longer than men but spend more of their lives in poor health, and they make 80% of healthcare decisions. Despite this influence, women’s health remains underfunded and understudied. Only about 4.5 % of total venture capital investment in health goes to women’s health companies, even though the opportunity is massive—closing the women’s health gap could unlock $1 trillion annually in global economic growth.
Poor care for women isn’t just a moral issue; it’s a systems failure with economic and social costs. “We’re not closing the health gap fast enough,” Ducach emphasizes. “If AI isn’t built responsibly, it’ll widen the divide.”
Ema’s purpose-built AI aims to close that divide by understanding women’s physiology, emotions, and communication patterns. Rather than replacing clinicians, the goal is to empower women to clearly express their symptoms, find care more quickly, and feel seen by the healthcare system.
Funding Challenges, Capital Efficiency, And AI Governance
For Ducach, building Ema has meant confronting two brutal realities: raising money as a woman founder and building technical credibility in the male-dominated world of AI. “When you’re a female founder building an AI company, not from Stanford or MIT, raising capital is an emotionally battling process.”
She has raised $3 million to date—an amount that might barely fund a prototype at many AI startups—but she used it to develop Ema’s proprietary hybrid language model and governance framework.
Lean efficiency is a hallmark of women-led venture-backed companies, which often accomplish more with less. “It forces focus and discipline,” Ducach shares. “We built something scalable without the waste that often comes with overfunding.”
Beyond capital, Ducach is tackling a quieter but equally pressing challenge: AI literacy. “Many CEOs don’t yet understand AI—how data security, bias monitoring, or governance fit into their business,” she shares. Her dual role—educating leaders and engineering the technology—has made Ema both a builder and a guide for ethical AI in healthcare.
Investors See Transformative Potential In AI-Powered Women’s Health
Investors are taking notice of Ema’s disciplined strategy and mission. “We chose to invest in Ema because of its potential to meaningfully transform women’s health through generative AI,” says James Roller, managing partner at Victorum Capital. “Amanda’s focus on defining an AI application that is focused on women transforms the accessibility and efficacy of a platform.”
That support underscores growing recognition that AI for women’s health isn’t a niche—it’s a catalyst for innovation in how healthcare serves half the population.
AI-Powered Women’s Health Built On Trust And Insight
The conversation around technology often centers on fairness, but Ducach frames her mission around representation—building tools that reflect and respect women’s lived experiences.
Folkendt’s warning about algorithmic bias isn’t an indictment of AI—it’s a call to do better. Ducach agrees. “If we build AI ethically,” she said, “it can be one of the greatest equalizers in healthcare. But only if women are part of designing it.”
Ema’s approach—clinical oversight, strict governance, and actual empathy baked into the system—shows that AI-powered women’s health doesn’t have to repeat medicine’s old mistakes. Done right, it can start closing gaps that have existed for generations.
